Results 71 to 80 of about 694,261 (269)

Pentagonal 2D Altermagnets: Material Screening and Altermagnetic Tunneling Junction Device Application

Advanced Functional Materials, EarlyView.
From a database of 170 pentagonal 2D materials, 4 candidates exhibiting altermagnetic ordering are screened. Furthermore, the spin‐splitting and unconventional boundary states in the pentagonal 2D altermagnetic monolayer MnS2 are investigated. A MnS2‐based altermagnetic tunneling junction is designed and, through ab initio quantum transport simulations,
Jianhua Wang, Xingyue Yang, Zongmeng Yang, Jing Lu, Pin Ho, Wenhong Wang, Yee Sin Ang, Zhenxiang Cheng, Shibo Fang   +8 more
wiley   +1 more source

For a learnable mathematics in the digital cultures [PDF]

, 2001
I begin with some general remarks concerning the co-evolution of representational forms and mathematical meanings. I then discuss the changed roles of mathematics and novel representations that emerge from the ubiquity of computational models, and ...
Noss, Richard
core   +1 more source

Structural results on convexity relative to cost functions

, 2012
Mass transportation problems appear in various areas of mathematics, their solutions involving cost convex potentials. Fenchel duality also represents an important concept for a wide variety of optimization problems, both from the theoretical and the ...
A. Karakhanyan, C.P. Niculescu, C.P. Niculescu, Daniel Alexandru Ion, Flavia-Corina Mitroi, H. Touchette, L. Rüschendorf, N. Trudinger, N. Trudinger, S.T. Rachev, W. Fenchel, W. Gangbo, X.-J. Wang, X.-N. Ma   +13 more
core   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Three‐dimensional Antimony Sulfide Based Flat Optics

Advanced Functional Materials, EarlyView.
This work presents the development of a grayscale electron beam lithography (g‐EBL) method for fabricating antimony trisulfide (Sb2S3) nanostructures with customizable 3D profiles. The refractive index of g‐EBL patterned Sb2S3 is determined based on the synergy of genetic algorithm and transfer matrix method.
Wei Wang, Uwe Hübner, Anne Gärtner, Tao Chen, Joseph Köbel, Franka Jahn, Daniel Repp, Abhrodeep Dey, Henrik Schneidwind, Andrea Dellith, Jan Dellith, Torsten Wieduwilt, Matthias Zeisberger, Tanveer Ahmed Shaik, Astrid Bingel, Markus A. Schmidt, Jer‐Shing Huang, Ulf Peschel, Volker Deckert   +18 more
wiley   +1 more source

Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics

Advanced Functional Materials, EarlyView.
Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha, Yingshan Ma, Yong Nam An, Sung‐Un An, Hyeon Hak Jung, Suvi‐Tuuli Varjamo, Jiwon Yoo, Junho Min, Hanvit Kim, Faisal Ahmed, Sang Hoon Chae, Young Min Song, Weiwei Cai, Tawfique Hasan, Zhipei Sun, Dong‐Ho Kang, Hyeon‐Jin Shin, Yunyun Dai, Hoon Hahn Yoon   +18 more
wiley   +1 more source

Riga – Plate flow of γ Al2O3-water/ethylene glycol with effective Prandtl number impacts

Heliyon, 2019
In many industrial processes, the cooling process can be improved by varying the flow geometry or changing the additives in the working fluid. The present work concentrates on the flow of γ Al2O3 –Water/Ethylene Glycol over a Gailitis and Lielausis ...
N. Vishnu Ganesh, Qasem M. Al-Mdallal, Sara Al Fahel, Shymaa Dadoa   +3 more
doaj   +1 more source

Smarter Sensors Through Machine Learning: Historical Insights and Emerging Trends across Sensor Technologies

Advanced Functional Materials, EarlyView.
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee, Osman Gul, Yeongjae Kwon, Jaeseok Jeong, Seokjoo Cho, Jihyeon Ahn, Jehee Yu, Cheolmin Kim, Donho Lee, Hyeonseok Han, Byeongju Lee, Jungrak Choi, Ji‐Hwan Ha, Yongrok Jeong, Kyungnam Kang, Ali Javey, Junseong Ahn, Inkyu Park   +17 more
wiley   +1 more source

Toward Scalable Solutions for Silver‐Based Gas Diffusion Electrode Fabrication for the Electrochemical Conversion of CO2 – A Perspective

Advanced Functional Materials, EarlyView.
In this study, the preparation techniques for silver‐based gas diffusion electrodes used for the electrochemical reduction of carbon dioxide (eCO2R) are systematically reviewed and compared with respect to their scalability. In addition, physics‐based and data‐driven modeling approaches are discussed, and a perspective is given on how modeling can aid ...
Simon Emken, K. Ashoke Raman, Alexander Bauer, Violeta Karyofylli, Eva Jodat, André Karl, Rüdiger‐A. Eichel   +6 more
wiley   +1 more source

Research Achievements Review Series no. 20 - Mathematics and computation research [PDF]

Computational mathematics, perturbed orbit three-body problem, and periodic trajectories solutions through computer ...

core   +1 more source